FIXED SCOPEone-off build
Ship a DynamoDB deployment, end to end.
Fixed scope, fixed price, senior-only team. Data modeling to production in 6-10 weeks.
FIXED SCOPE
- Zero juniors on client work
- Fixed quote in week 1
- Code, infra, runbook — yours
DynamoDB Development Services.Single Digit Latency, Zero Ops.
Our Amazon DynamoDB development services and consulting exist for applications where single-digit latency at millions of requests per second isn't optional. Access patterns modeled before the first table gets created. Partition keys that distribute evenly, not ones that create hot partitions and throttle at 30% of provisioned capacity. We build on DynamoDB with the data modeling discipline that turns a serverless database into a predictable one.
- Single-table design
- Sub-5ms reads
- On-demand
- Zero hot partitions
Why Entalogics for DynamoDB
What every DynamoDB
development company
should model before creating a table.
Every DynamoDB table we audit has the same problems — a partition key chosen by field name instead of access pattern, five GSIs where two would do, scan operations sitting on hot paths because nobody modeled the query first. DynamoDB is simple to start. It's not simple to get right.
Data Model01
The schema got designed like a relational table, and DynamoDB punished it immediately.
DynamoDB inverts the usual order — you design for your queries first, entities second. We document every access pattern before a table exists. Every key, every GSI, every sort key has to be justified by a real query the application actually makes.
Partition Key02
A field-name partition key turned into throttling at 30% of provisioned capacity.
A bad partition key creates hot partitions that throttle long before the table's real capacity is reached. We model for high cardinality and even distribution — composite keys, write sharding, hierarchical keys wherever a single attribute won't spread the load evenly enough.
Cost03
On-demand pricing was quietly costing three to four times what provisioned would.
On-demand for genuinely unpredictable traffic. Provisioned with reserved capacity for stable baselines, at a fraction of the per-request cost. We measure the actual traffic pattern and pick the mode that matches it, with GSIs sized using sparse projections instead of ALL.
Architecture04
Single-table design got applied everywhere, including where it made onboarding worse.
Single-table design co-locates related data for fewer round trips — and it also raises complexity and can bloat GSIs when applied indiscriminately. We use it where entities are genuinely related and reach for separate tables where independent scaling actually matters more.
When DynamoDB, when not
DynamoDB is a tool.
Not always the right database.
DynamoDB delivers predictable millisecond latency at any scale with zero operational overhead — and it punishes a bad data model harder than any relational database ever will. We'll tell you honestly on the first call if DynamoDB fits.
PICK DYNAMODB WHEN
- Predictable sub-10ms latency at scale is the actual requirement DynamoDB was purpose-built for
- Serverless architecture matters — zero capacity planning, zero server management, pay-per-request
- Access patterns are simple — key-value lookups, range queries, time-series data
- High write throughput is real — millions of writes per second with on-demand scaling
CONSIDER ALTERNATIVES WHEN
- Complex queries with joins and aggregations are core — PostgreSQL or Aurora handles this natively
- Ad-hoc analytics is the goal — DynamoDB isn't a query engine, Athena or Redshift fits better
- Referential integrity matters — DynamoDB has no foreign keys to enforce it
- The dataset is small with predictable traffic — managed PostgreSQL costs less and stays more flexible
WE SAY NO WHEN
- "DynamoDB because it's serverless" — serverless is a deployment model, not a data modeling reason
- "Migrate our relational database to DynamoDB" — relational data rarely maps cleanly to NoSQL
- "We'll figure out access patterns later" — DynamoDB punishes that harder than any other database will
What we build on DynamoDB
DynamoDB development services
and consulting we deliver.
Eight ways this work shows up for real clients. Each one modeled for access patterns from day one.
- S01
Serverless application backends
Serverless application backendsLambda plus DynamoDB for event-driven APIs. Single-table design co-locating related entities. Sub-5ms reads on every hot path.
DYNAMODBLAMBDAAPI GATEWAYSINGLE-TABLE - S02
IoT and time-series ingestion
IoT and time-series ingestionMillions of events per second with composite partition keys distributing writes evenly. TTL for automatic expiration, DynamoDB Streams for real-time processing.
DYNAMODBSTREAMSTTLKINESIS - S03
Multi-tenant SaaS data architecture
Multi-tenant SaaS data architectureTenant-isolated data with tenant ID as the partition key prefix. Per-tenant query scoping without cross-partition reads. GSIs for admin-level views.
DYNAMODBSINGLE-TABLEGSIIAM - S04
Session and cache stores
Session and cache storesDynamoDB as a managed session store or cache layer. TTL for auto-expiry, DAX for microsecond read caching on the hottest items.
DYNAMODBDAXTTLSESSION STORE - S05
DynamoDB migration services
DynamoDB migration servicesSQL data remodeled for DynamoDB access patterns. Entities denormalized, relationships handled through composite keys and GSIs. Migration validated against real performance numbers.
DATA MODELINGMIGRATIONSINGLE-TABLEDMS - S06
DynamoDB cost optimization
DynamoDB cost optimizationExisting tables with throttling or runaway costs. Partition key analysis, GSI consolidation, capacity mode right-sizing, reserved capacity applied wherever the workload is stable.
CONTRIBUTOR INSIGHTSRESERVED CAPACITYGSI TUNINGCOST - S07
DynamoDB training and mentoring
DynamoDB training and mentoringHands-on training for engineering teams on access pattern modeling, single-table design, and the partition key discipline that keeps a table predictable long after we hand it off.
NOSQL WORKBENCHACCESS PATTERNSDOCUMENTATIONHANDOFF - S08
DynamoDB support and maintenance
DynamoDB support and maintenanceOngoing capacity monitoring, GSI reviews, and cost audits — so the table we optimized doesn't quietly drift back into the throttling and runaway cost we were hired to fix.
CLOUDWATCHCONTRIBUTOR INSIGHTSCOST EXPLORERSUPPORT
The playbook
DynamoDB development
patterns we ship on repeat.
Patterns from real production tables, not workshop exercises.
P01
Access patterns documented before table creation
Every query listed. Every key justified. Every GSI mapped to a real access pattern. No table gets created on an assumption.
P02
Composite keys for item collections
Related entities share a partition key. Sort key distinguishes type and enables range queries. One Query call returns everything a screen needs.
P03
Sparse GSIs over full projections
GSIs project only the attributes a query actually needs. Items missing those attributes don't appear in the index. Less storage, less write amplification, lower cost.
P04
DynamoDB Streams for materialized views
Write to one table, stream changes to Lambda, write denormalized views to another table or GSI. Every hot-path query reads from a pre-computed structure.
P05
Contributor Insights for hot partition detection
Enabled on every production table. Most-accessed partition keys visible in real time. Hot partitions caught before they throttle, not after.
P06
Reserved capacity for stable workloads
Provisioned mode with reserved capacity for predictable baselines. On-demand for spiky traffic. Mixed across tables based on actual usage, not a blanket policy.
Signature case
An e-commerce backend,
remodelled from scan-heavy to partition-aligned.
A B2C e-commerce platform on DynamoDB — scan operations on the product listing page, five GSIs with ALL projections, on-demand pricing at $4,800/mo, and throttling on the order table during flash sales. Remodelled to single-table design with sparse GSIs, switched hot tables to provisioned with reserved capacity, eliminated all scan operations in 7 weeks. Monthly cost dropped to $1,900. Zero throttling during the next flash sale.
Before
Scan on product listing · 5 GSIs with ALL projection · on-demand $4,800/mo · throttling during sales
After
Query-only, partition-aligned · 2 sparse GSIs · provisioned + reserved $1,900/mo · zero throttling
- Monthly cost−60%
- Scans eliminated100%
- Flash sale throttling0
- To fully remodelled7wk
Industries we serve
DynamoDB development
across industries.
We've delivered DynamoDB development services for eCommerce, gaming, IoT, and multi-tenant SaaS platforms — anywhere millisecond latency at unpredictable scale genuinely matters more than complex querying.
- eCommerce & Retail
- Gaming & Social
- IoT & Telemetry
- SaaS & Multi-Tenant
- Media & Streaming
- FinTech
Engagement shape
Eight to ten weeks
on a DynamoDB engagement.
Table by table. The current data stays live the entire time we work.
- W01
Audit + RFC
Two senior DynamoDB engineers. Access pattern analysis, partition key audit, GSI review, capacity mode assessment. A ranked, dollarized plan.
- W02–03
Data model + first table
Access patterns modeled, keys designed, GSIs defined, first table deployed with SDK integration. Real throughput measured.
- W04–08
Table by table
Each table modeled, migrated, and validated. Streams wired. Capacity mode optimized. Your application keeps running throughout.
- W09+
Handoff
Contributor Insights enabled, cost dashboard live. Runbook handed to your team — or we stay on for DynamoDB support and maintenance.
Stack
Tools we
Tools we reach
reach for for first.
Our default DynamoDB development stack — picked for production.
Database
DynamoDB · DAX · DynamoDB Streams · Global Tables
SDK
AWS SDK V3 (JS) · Boto3 (Python) · AWS SDK (.NET) · AWS SDK (Java)
Modelling
NoSQL Workbench · Single-table design · Access pattern mapping
Cost
Contributor Insights · Reserved Capacity · CloudWatch · Cost Explorer
Migration
AWS DMS · Custom migration scripts · DynamoDB Streams
Monitoring
CloudWatch · Contributor Insights · Datadog · X-Ray
Engagement
Three ways to hire
DynamoDB developers
at Entalogics.
No hourly billing for thinking time. Fixed quote or a transparent monthly rate.
DEDICATED TEAMmonthly
Hire dedicated DynamoDB developers.
Senior data architects specializing in DynamoDB modeling, embedded in your team. Pause, resize, or exit with 30 days' notice.
PER ENGINEER
- Same senior bar as fixed-scope
- Embedded in your team
- Founder-direct escalation
ENGAGEMENTcustom
Strategic DynamoDB consulting partnership.
A standing partner for serverless data — cost optimization, single-table architecture, migration strategy, team training, hiring help.
PROCUREMENT-FRIENDLY
- Multi-quarter roadmap
- Architecture and hiring partner
- Procurement-friendly paper
FAQ
DynamoDB development —
questions we get on every call.
Single-table vs multi-table, throttling, capacity mode, cost, training — in roughly the order people ask.Single-table when related entities are frequently queried together — user plus orders, tenant plus resources. Multi-table when entities scale independently or need different capacity profiles. Most applications end up using a mix. We model based on your actual access patterns, not a dogma.
Hot partitions. One partition key value is absorbing most of the traffic while others sit idle. DynamoDB's per-partition limit applies regardless of the table's overall provisioned capacity. Fix the partition key distribution and the throttling disappears.
On-demand for unpredictable or spiky traffic. Provisioned with reserved capacity for stable baselines, at a fraction of the cost. Most production workloads end up provisioned on hot tables and on-demand on cold ones.
A typical engagement runs $15K-$30K over 6-10 weeks, depending on table count and whether it's new modeling or migrating an existing schema. The week-one audit gives you real numbers specific to your workload.
Yes. We train engineering teams on access pattern modeling, single-table design, and the partition key discipline that keeps a table healthy long after the engagement ends.
Yes. We audit partition keys, GSI projections, capacity modes, and access patterns. Most existing deployments have 30-60% cost reduction available without any application code changes.
Founder-direct
Tell us whatyou're building.
Thirty minutes with the founder — a senior DynamoDB engineer, the relevant playbook, and a candid read on whether DynamoDB is the right database, or PostgreSQL, Aurora, or Cosmos DB fits your workload better.